391 data-"https:"-"https:"-"https:"-"https:"-"CEA-Saclay" PhD positions in United Kingdom
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Field
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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from the establishment fund for Prof Gary Williamson, who recently joined Queen’s from Australia. The position is to generate data in the area of polyphenols and health and publish high quality papers
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and colleagues located across the 4 nations of the UK. HDR UK’s mission is to unite the UK’s health data to enable discoveries that improve people’s lives. Its 20-year vision is for large-scale data and
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These are extraordinary times for research in gravitational waves and cosmology. A wealth of new data from cutting-edge observatories is transforming our understanding of the Universe, opening
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to better predict incident disease from high-dimensional genetic and non-genetic data, quantification of trait heterogeneity and asymmetry from imaging data, leveraging biobank genetic and prescription data
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into its latest Ryzen processors, unlocking new possibilities for on-device AI acceleration. This project aims to maximise the potential of AMD’s cutting-edge hardware for healthcare computer vision
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, biologging, and coding) to map and analyse complex burrow structures and their usage at our established field-site in South Africa. You will combine this with long-term behavioural and life-history data from
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energy research, combining laboratory experimentation, computational modelling, and data analysis. Experimental work will be carried out in the world class COAST laboratory, examining floating offshore
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, maintenance logistics, and weather-related downtime for offshore wind assets. Drawing on climate projections, metocean datasets, and offshore O&M modelling techniques, the research will develop data-informed